CN111788567A

CN111788567A - A data processing device and a data processing method

Info

Publication number: CN111788567A
Application number: CN201880090383.2A
Authority: CN
Inventors: 许若圣
Original assignee: Huawei Technologies Co Ltd
Current assignee: Huawei Technologies Co Ltd
Priority date: 2018-08-27
Filing date: 2018-08-27
Publication date: 2020-10-16
Anticipated expiration: 2038-08-27
Also published as: WO2020041934A1; CN111788567B

Abstract

The embodiment of the application discloses data processing equipment, which is used for realizing parallel processing of data and reducing data processing time delay by arranging a parameter determining module and a neural network computing module coupled with the parameter determining module which are mutually independent. The method in the embodiment of the application comprises the following steps: a data processing apparatus, the data processing apparatus comprising: a parameter determination module and a neural network computation module coupled to the parameter determination module; the parameter determining module is used for performing parameter calculation on the first data to obtain a first parameter set for calculating the first neural network; the neural network calculation module is used for performing the first neural network calculation on the first data by using the first parameter set to obtain a calculation result; wherein the parameter calculation of the parameter determination module is independent of the first neural network calculation of the neural network calculation module.

Description

PCT国内申请，说明书已公开。PCT domestic application, the description has been published.

Claims

A data processing apparatus, characterized by comprising: a parameter determination module and a neural network computation module coupled to the parameter determination module;

the parameter determining module is used for performing parameter calculation on the first data to obtain a first parameter set for calculating the first neural network;

the neural network calculation module is used for performing the first neural network calculation on the first data by using the first parameter set to obtain a calculation result; wherein,

the parameter calculation of the parameter determination module is independent of the first neural network calculation of the neural network calculation module.
The parameter determination module of claim 1, wherein the parameter determination module is specifically configured to perform the parameter calculation on the first data using a second neural network to obtain the first parameter set.
The parameter determination module according to claim 1 or 2, wherein the parameter determination module is specifically configured to:

performing parameter calculation on the first data to obtain a second parameter set;

and processing the second parameter set and a third parameter set to obtain the first parameter set, wherein the third parameter set is a historical parameter set calculated by the parameter determination module.
The parameter determination module according to any of claims 1 to 3, wherein the performing a parameter calculation on the first data comprises: and carrying out matrix operation on the first data and a preset matrix.
The parameter determination module of any one of claims 1 to 4, wherein the parameter determination module is operable to perform the calculation of the parameter on second data that is temporally earlier than the first data when the neural network calculation module is in the state of the first neural network calculation.
The parameter determination module according to any of claims 1 to 5, wherein the first set of parameters comprises: a quantization parameter or an adjustment amount of the quantization parameter or a parameter associated with the quantization parameter;

the first neural network computation is a quantized neural network computation.
A method of data processing, the method comprising:

performing parameter calculation on the first data through a parameter determination module to obtain a first parameter set for calculating the first neural network;

performing, by a neural network calculation module, the first neural network calculation on the first data by using the first parameter set to obtain a calculation result; wherein,

the parameter calculation of the parameter determination module is independent of the first neural network calculation of the neural network calculation module.
The method of claim 7, wherein the performing a parameter calculation on the first data comprises:

and performing parameter calculation on the first data by utilizing a second neural network.
The method of claim 7 or 8, wherein said performing said parameter calculation on said first data to obtain said first set of parameters comprises:

performing parameter calculation on the first data to obtain a second parameter set;

and processing the second parameter set and a third parameter set to obtain the first parameter set, wherein the third parameter set is a historical parameter set calculated by the parameter determination module.
The method of any of claims 7 to 9, wherein the performing a parameter calculation on the first data comprises:

and carrying out matrix operation on the first data and the preset matrix.
The method according to any one of claims 7 to 10, further comprising:

when the neural network calculation module is in a state of the first neural network calculation, the parameter determination module calculates parameters of second data, and the second data is earlier than the first data in a time domain.
The method according to any of claims 7 to 11, wherein the first set of parameters comprises: a quantization parameter or an adjustment amount of the quantization parameter or a parameter associated with the quantization parameter;

the first neural network computation is a quantized neural network computation.